本論文旨在鑑別批次式輪蟲養殖的增殖模型之參數，並利用此模型進行輪蟲增殖的預測。
將輪蟲不同帶卵情形的密度當作狀態變數，採用一階線性的隨機模型來建立輪蟲增殖模型。輪蟲增殖模型的參數則是使用即時最小平方參數估測的演算法來求得。
利用此模型分別以時間間隔為1小時、12小時和24小時來預測下一時間間隔的輪蟲狀態，並且就不同的遺忘因子λ對預測的效果加以分析。在時間間隔為1小時之預測結果顯示，應選擇λ=0.97至1.00較佳；就輪蟲養殖初期至後指數前期範圍內，在時間間隔為12或24小時之預測，應選擇λ=0.97至1.00較好，若涵蓋四個生長期等具有較大變動的增殖情形下，則在時間間隔為12小時之情況應選擇λ=0.91至0.93較好，時間間隔為24小時應選擇λ=0.91較好。
將鑑別所得的參數應用於另一組實驗上，在第96小時時誤差仍能維持在4.42%至11.17%範圍內，顯示估測的參數可以應用在另一次養殖的預測上。

This thesis identified the parameters of growth model and predicted the production for the batch culture of rotifers.
The growth rate of rotifers was modeled by a first-order linear stochastic model with the densities of rotifers carrying multiple, single or no egg as state variables. The parameters of the growth model for rotifers were estimated by real-time recursive least-squares (RLS) algorithm.
Parameters were identified and production was predicted for the cases of time interval 1, 12, and 24 hours. The effects of forgetting factorsλwere also investigated. Better results were obtained with forgetting factorλbetween 0.97 and 1.00 in the cases of 1-hour time interval prediction. During the beginning and fore post-exponential phase, forgetting factorλranging between 0.97 and 1.00 was better in 12 or 24-hour time interval prediction. For more fluctuant cases such as processes throughout 4 phases, λ=0.91 to 0.93 was more adequate in 12-hour time interval andλ=0.91 in 24-hour time interval.
Parameters obtained from the foregoing experiment could be applied to predict the result of another experiment. Prediction errors could remain between 4.42% and 11.47% within 96 hours.

第一章前言1
1.1簡介1
1.2研究目的3
第二章文獻探討4
2.1輪蟲增殖性質4
2.2生物系統鑑別6
2.2.1生物系統與數學模式6
2.2.2系統鑑別7
2.3一般生物生長模式9
2.3.1Monod-Herbert模式9
2.3.2其他生長模式11
2.3.3輪蟲族群動態分析11
2.4隨機模式13
2.4.1MA模式13
2.4.2AR模式14
2.4.3ARMA模式15
2.4.4ARMAX模式15
2.5最小平方估測15
2.5.1統計特性16
2.5.2最小平方估測17
2.5.3遞迴最小平方估測20
2.5.4即時最小平方估測28
第三章材料與方法33
3.1輪蟲養殖33
3.1.1輪蟲種源33
3.1.2輪蟲養殖環境及設備33
3.1.3輪蟲餵飼36
3.2輪蟲取樣36
3.3輪蟲增殖模式建構與分析38
3.3.1一階差分方程式模式38
3.3.2輪蟲狀態空間模式分析39
3.3.3模式時間間隔的選取46
3.4輪蟲增殖預測47
3.5程式撰寫48
第四章結果與討論51
4.1輪蟲養殖51
4.2輪蟲增殖模式鑑別與預測59
4.2.1參數鑑別結果59
4.2.2輪蟲增殖預測61
4.3遺忘因子對輪蟲增殖預測的影響67
4.3.1誤差評量指標67
4.3.2實驗I預測分析73
4.3.3實驗II預測分析83
4.3.4實驗III預測分析92
4.3.5遺忘因子的選擇97
4.4以鑑別所得參數預測其他實驗的結果98
第五章結論與建議107
5.1結論107
5.2建議109
參考文獻..111
附錄　電腦程式117

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